Zholtkevych G N, Bespalov G Yu, Nosov K V, Abhishek Mahalakshmi
V. N. Karazin Kharkiv National University, Svobody sqr., 4, Kharkiv, 61077, Ukraine,
Acta Biotheor. 2013 Dec;61(4):449-65. doi: 10.1007/s10441-013-9184-6. Epub 2013 Aug 10.
Mathematical modeling is a convenient way for characterization of complex ecosystems. This approach was applied to study the dynamics of zooplankton in Lake Sevan (Armenia) at different stages of anthropogenic eutrophication with the use of a novel method called discrete modeling of dynamical systems with feedback (DMDS). Simulation demonstrated that the application of this method helps in characterization of inter- and intra-component relationships in a natural ecosystem. This method describes all possible pairwise inter-component relationships like "plus-plus," "minus-minus," "plus-minus," "plus-zero," "minus-zero," and "zero-zero" that occur in most ecosystems. Based on the results, a working hypothesis was formulated. It was found that the sensitivity to weak external influence in zooplanktons was the greatest during the mid period of eutrophication in Lake Sevan, whereas in the final stages of eutrophication, an outbreak in the biomass production of cyanobacteria was evident. To support this approach, a weak external disturbance in the form of magnetic storm was used to see its effect on species Daphnia longispina sevanica. A statistically significant correlation between the frequency of magnetic storms and the number of this species was revealed and an increase in the number of toxic cyanobacteria species as a consequence of eutrophication. This paper, for the first time, suggests a DMDS method, to diagnose impact of anthropogenic eutrophication on environment.
数学建模是表征复杂生态系统的一种便捷方式。这种方法被应用于研究塞凡湖(亚美尼亚)在人为富营养化不同阶段浮游动物的动态变化,采用了一种名为带反馈的动态系统离散建模(DMDS)的新方法。模拟结果表明,该方法有助于表征自然生态系统中各组分之间以及组分内部的关系。该方法描述了大多数生态系统中出现的所有可能的成对组分间关系,如“正正”“负负”“正负”“正零”“负零”和“零零”。基于这些结果,提出了一个可行的假设。研究发现,在塞凡湖富营养化中期,浮游动物对微弱外部影响的敏感度最高,而在富营养化的最后阶段,蓝藻生物量产量出现爆发式增长。为支持这一方法,以磁暴形式施加微弱外部干扰,观察其对长刺塞凡水蚤物种的影响。结果揭示了磁暴频率与该物种数量之间存在统计学上的显著相关性,以及富营养化导致有毒蓝藻物种数量增加。本文首次提出了一种DMDS方法,用于诊断人为富营养化对环境的影响。